A method of stochastic dominance analysis with respect to a function (SDRF) is described and illustrated. The method, called stochastic efficiency with respect to a function (SERF), orders a set of risky alternatives in terms of certainty equivalents for a specified range of attitudes to risk. It can be applied for conforming utility functions with risk attitudes defined by corresponding ranges of absolute, relative or partial risk aversion coefficients. Unlike conventional SDRF, SERF involves comparing each alternative with all the other alternatives simultaneously, not pairwise, and hence can produce a smaller efficient set than that found by simple pairwise SDRF over the same range of risk attitudes. Moreover, the method can be implemented in a simple spreadsheet with no special software needed.

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Simulation as an analytical tool continues to gain popularity in industry, government, and academics. For agricultural economists, the popularity is driven by an increased interest in risk management tools and decision aids on the part of farmers, agribusinesses, and policy makers. Much of the recent interest in risk analysis in agriculture comes from changes in the farm program that ushered in an era of increased uncertainty. With increased planting flexibility and an abundance of insurance and marketing alternatives farmers face the daunting task of sorting out many options in managing the increased risk they face. Like farmers, decision makers throughout the food and fiber industry are seeking ways to understand and manage the increasingly uncertain environment in which they operate. The unique abilities of simulation as a tool in evaluating and presenting risky alternatives together with an expected increase in commodity price risk, as projected by Ray, et al., will likely accelerate the interest in simulation for years to come.